Urban Expansion and Satellite–Administrative Divergence in Mongolia: Multi-Sensor Evidence from Ulaanbaatar and Pastoral Provinces

Urban monitoring in rapidly growing dryland cities is difficult because satellite signals and administrative records capture different aspects of settlement change and can perform differently across land-cover contexts. Mongolia provides a useful case because urban growth is concentrated in Ulaanbaatar while pastoral provinces remain exposed to ecological and livelihood shocks. We integrate MODIS NDVI, CHIRPS-derived SPI_12, a harmonized DMSP-OLS/VIIRS nighttime-light series, and administrative livestock and migration data for 22 spatial units over 2000–2024 (N = 550). A planned Landsat BuiltUp component was tested against Dynamic World for 2016–2024 (N = 39,600). The frozen NDBI > 0 and NDVI < 0.2 rule failed transfer validation (balanced accuracy = 0.474, Kappa = −0.052, F1 = 0.408; bare-to-built false-positive rate = 0.949), and enriched spectral models retained material province-specific errors. No repaired BuiltUp classifier was therefore frozen, and the original UEI, Mismatch, Ulaanbaatar M3, and spatial UEI analyses are not retained as principal evidence. In the retained origin-side panel, lower lagged NDVI anomaly is associated with greater livestock loss (β = −0.0148, p = 0.016), dzud severity with greater loss (β = 0.00454, p = 0.034), and higher prior-year livestock loss with higher standardized registered out-migration pressure (β = 1.113, p < 0.001). Nighttime-light harmonization shows strong level agreement but weaker rank continuity around the sensor transition. The study therefore advances a validation-first multi-source monitoring framework that withdraws unsupported urban composites after a failed measurement gate.